Search bioRxiv⌕ Search

Biology subjects

Tao, P.

Publications and source records attributed to Tao, P..

At least 19 recordsLinked to original sources

A Cytokine Receptor Signaling Atlas Reveals How STAT Mosaics Fine-Tune T Cell Function

The extent to which JAK/STAT cytokine signaling is functionally redundant or selective remains debated. Here we engineered a double orthogonal IL-2/IL-2R{beta}/{gamma}c ternary system enabling programmable, interference-free activation of each of the 36 mammalian cytokine receptors, and their downstream six STATs, in T cells. At the membrane-proximal level, comprehensive phospho-signaling profiling revealed that while each receptor activates a dominant STAT, unique STAT activation fingerprints derived from combinatorial biases fine-tune nuanced T cell fates. At the membrane-distal level, single-cell transcriptomic atlas of all cytokine receptors confirmed that these STAT mosaics sensitively specify non-redundant transcriptional programs. STAT5-dominant receptors drove proliferative expansion at the expense of stemness; STAT3-driven programs instructed a continuum from stem cell memory to terminal effector states with preserved cytotoxic capacity and mediated superior curative antitumor responses; while other STATs specified highly restricted phenotypes. These findings decode a STAT signaling vocabulary that defines the intrinsic functional bandwidth of natural cytokines.

immunology↗

All-by-All Cytokine Receptor Pairing Network Unlocks Coding of Non-Natural T Cell States

Cytokine receptor pairing rules, set by evolution, confine JAK-STAT signaling to a narrow region of a far larger combinatorial space. Of more than 1,200 pairings theoretically possible among the [~]36 JAK-associated human cytokine receptors, only [~]30-40 exist in nature. Using a double-orthogonal platform, we enforced pairings across the full all-by-all receptor matrix and resolved a fine-grained STAT atlas richer than the natural repertoire. Selected non-natural pairings generated emergent T cell states unpredictable from either parental receptor, with pairing orientation encoding signaling specificity. A synthetic IL-21R>IL-2R{beta} pairing, but not its reciprocal, drove a cytotoxic Tc17-like state, whereas natural IL-9R/{gamma}c drove a Tc1 fate despite similar STAT activation, showing that rebalancing quantitative STAT combinatorics can modulate T cell fate. Recombining IL-31R, not expressed in T cells, with STAT-biased receptor partners generated diverse states, several with superior antitumor efficacy. These findings define a non-natural pairing code for engineering synthetic T cell fates.

immunology↗

The emergent mental operation of the learning brain

How does the learning brain give rise to emergent mental operations that enable skill internalization and generalization? Using five-year longitudinal tracking of children acquiring abacus-based mental calculation, we reveal how sustained practice progressively reconfigures whole-brain states. Learning induces nonlinear transitions from stable baseline configurations through a transient exploratory phase toward restabilized associative brain networks. This hierarchical remodeling cascades from perceptual systems to action and default networks, mediated by adaptive neural variability and selective connectivity reweighting, with the salience-parietal memory network acting as a dynamic relay. These brain-state transitions accompany an ordered cognitive transfer cascade, emerging within arithmetic and extending to visuospatial and executive functions. Our findings are reproducible and provide a systems-level account of how ecological learning sculpts large-scale networks to enable complex skill acquisition.

neuroscience↗

Periplasmic gatekeeping of phage DNA entry by rSAM enzyme-mediated maturation of an effector with His-X-Ser repeats

In the relentless arms race between bacteria and phages, bacteria have evolved a variety of defense strategies to combat phage infection. However, no bacterial system has been identified that specifically target the phage DNA entry phase. Here, we present a novel bacterial antiphage system, termed HXS, which provides broad-spectrum and robust antiphage activity by interfering with phage DNA entry. The HXS system consists of two radical S-adenosylmethionine (rSAM) enzymes (HxsB and HxsC), a small protein (HxsD), and the effector HxsA with a peptidoglycan-binding domain and five His-Xaa-Ser (HXS) repeats. HxsB/HxsC catalyze rSAM enzyme-dependent maturation of HxsA, including N-terminal processing and a site-specific +8 Da modification, thereby producing a periplasmic effector required for HXS defense. Biochemical evidence supports a model in which the matured effector likely engages incoming DNA electrostatically to arrest entry, establishing an rSAM enzyme-modified protein effector in antiphage defense.

microbiology↗

Angular Deviation Diffuser: A Transformer-Based Diffusion Model for Efficient Protein Conformational Ensemble Generation

Protein functionality is inherently tied to its structure, with both static and dynamic conformations playing critical roles in defining biological activity. While molecular dynamics (MD) simulations have long been the standard for exploring protein dynamics, they come with high computational costs and limited sampling efficiency. Recent advances in deep learning, such as AlphaFold, have significantly improved static protein structure prediction, yet accurately generating the dynamic ensemble of protein conformations remains a complex challenge. In this study, we present a transformer-based diffusion model that generates diverse conformational ensembles of protein backbones by utilizing angular deviations as data flow. Our model combines a cutting-edge diffusion model with the principles of SE(3) symmetry to enhance both the accuracy and efficiency of conformational sampling. Applied to the Vivid (VVD) Photoreceptor protein system, the generated ensembles closely align with those from MD simulations while covering a broader range of conformational states. This approach offers an improved methodology for capturing protein dynamics, contributing to a more comprehensive understanding of protein structure and function.

bioinformatics↗

Accurate Characterization of the Allosteric Energy Landscapes, Binding Hotspots and Long-Range Communications for KRAS Complexes with Effector Proteins : Integrative Approach Using Microsecond Molecular Dynamics, Deep Mutational Scanning of Binding Energetics and Allosteric Network Modeling

KRAS is a pivotal oncoprotein that regulates cell proliferation and survival through interactions with downstream effectors such as RAF1. Oncogenic mutations in KRAS, including G12V, G13D, and Q61R, drive constitutive activation and hyperactivation of signaling pathways, contributing to cancer progression. Despite significant advances in understanding KRAS biology, the structural and dynamic mechanisms of KRAS binding and allostery by which oncogenic mutations enhance KRAS-RAF1 binding and signaling remain incompletely understood. In this study, we employ microsecond molecular dynamics simulations, Markov State Modeling, mutational scanning and binding free energy calculations together with dynamic network modeling to elucidate the effect of KRAS mutations and characterize the thermodynamic and allosteric drivers and hotspots of KRAS binding and oncogenic activation. Our simulations revealed that oncogenic mutations stabilize the open active conformation of KRAS by differentially modulating the flexibility of the switch I and switch II regions, thereby enhancing RAF1 binding affinity. The G12V mutation rigidifies both switch I and switch II, locking KRAS in a stable, active state. In contrast, the G13D mutation moderately reduces switch I flexibility while increasing switch II dynamics, restoring a balance between stability and flexibility. The Q61R mutation induces a more complex conformational landscape, characterized by the increased switch II flexibility and expansion of functional macrostates, which promotes prolonged RAF1 binding and signaling. Mutational scanning of KRAS-RAF1 complexes identified key binding affinity hotspots, including Y40, E37, D38, and D33, and together with the MM-GBSA analysis revealed the hotspots leverage synergistic electrostatic and hydrophobic binding interactions in stabilizing the KRAS-RAF1 complexes. Network-based analysis of allosteric communication identifies critical KRAS residues (e.g., L6, E37, D57, R97) that mediate long-range interactions between the KRAS core and the RAF1 binding interface. The central {beta}-sheet of KRAS emerges as a hub for transmitting conformational changes, linking distant functional sites and facilitating allosteric regulation. Strikingly, the predicted allosteric hotspots align with experimentally identified allosteric binding hotspots that define the energy landscape of KRAS allostery. This study highlights the power of integrating computational modeling with experimental data to unravel the complex dynamics of KRAS and its mutants. The identification of binding hotspots and allosteric communication routes offers new opportunities for developing targeted therapies to disrupt KRAS-RAF1 interactions and inhibit oncogenic signaling. Our results underscore the potential of computational approaches to guide the design of allosteric inhibitors and mutant-specific therapies for KRAS-driven cancers.

biophysics↗

IL-9 as a naturally orthogonal cytokine with optimal JAK/STAT signaling for engineered T cell therapy

Arming T cells with a synthetically orthogonal IL-9 receptor (o9R) permits facile engraftment and potent anti-tumor functions. We considered whether the paucity of natural IL-9R expression could be exploited for T cell immunotherapy given that, in mice, high doses of IL-9 were well-tolerated without discernible immune modulation. Compared to o9R, T cells engineered with IL-9R exhibit superior tissue infiltration, stemness, and anti-tumor activity. These qualities are consistent with a stronger JAK/STAT signal, which in addition to STAT1/3/5, unexpectedly includes STAT4 (canonically associated with IL-12 but not common {gamma}-chain cytokines). IL-9R T cells are exquisitely sensitive to perturbations of proximal signaling, including structure-guided attenuation, amplification, and rebalancing of JAK/STAT signals. Biased IL-9R mutants uncover STAT1 as a rheostat between proliferative stem-like and terminally differentiated effector states. In summary, we identify native IL-9/IL-9R as a natural cytokine-receptor pair with near-orthogonal qualities and an optimal JAK/STAT signaling profile for engineered T cell therapy.

immunology↗

A Modular Bacteriophage T4 Nanoparticle Platform Enables Rapid Design of Completely Protective Multivalent Mucosal Dual Vaccine Against COVID-19 and Flu

A multivalent, rapidly deployable, mucosal vaccine platform is desperately needed to prevent the acquisition and transmission of respiratory infections during epidemics and pandemics. We present one such bacteriophage T4-based platform, and design of dual COVID-19-Flu mucosal vaccines by exploiting its unique architecture. These include: T4s natural affinity for nasal mucosa, flexible engineering to incorporate multiple antigens, and repeat and symmetric epitope presentation for enhanced B cell responses. Hundreds of SARS-CoV-2 spike trimers and nucleocapsid proteins, and influenza hemagglutinin trimers and M2e peptides, were incorporated into a single phage, creating the highest density nanoparticle presentation yet reported. Intranasal administration of adjuvant-free vaccine induced robust mucosal immunity in mice including, neutralizing antibody and secretory IgA, lung-resident CD4+/CD8+ T cells, diverse memory B cells, and complete protection against SARS-CoV-2 and influenza challenges. The noninfectious T4 phage offers an extraordinary platform to rapidly design potent mucosal vaccines against emerging bacterial and viral threats.

microbiology↗

Prediction of Conformational Ensembles and Structural Effects of State-Switching Allosteric Mutants in the Protein Kinases Using Comparative Analysis of AlphaFold2 Adaptations with Sequence Masking and Shallow Subsampling

Despite the success of AlphaFold2 approaches in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and have been challenged to accurately capture of the effects of single point mutations that induced significant structural changes. We systematically examined several implementations of AlphaFold2 methods to predict conformational ensembles for state-switching mutants of the ABL kinase. The results revealed that a combination of randomized alanine sequence masking with shallow multiple sequence alignment subsampling can significantly expand the conformational diversity of the predicted structural ensembles and capture shifts in populations of the active and inactive ABL states. Consistent with the NMR experiments, the predicted conformational ensembles for M309L/L320I and M309L/H415P ABL mutants that perturb the regulatory spine networks featured the increased population of the fully closed inactive state. On the other hand, the predicted conformational ensembles for the G269E/M309L/T334I and M309L/L320I/T334I triple ABL mutants that share activating T334I gate-keeper substitution are dominated by the active ABL form. The proposed adaptation of AlphaFold can reproduce the experimentally observed mutation-induced redistributions in the relative populations of the active and inactive ABL states and capture the effects of regulatory mutations on allosteric structural rearrangements of the kinase domain. The ensemble-based network analysis complemented AlphaFold predictions by revealing allosteric mediating centers that often directly correspond to state-switching mutational sites or reside in their immediate local structural proximity, which may explain the global effect of regulatory mutations on structural changes between the ABL states. This study suggested that attention-based learning of long-range dependencies between sequence positions in homologous folds and deciphering patterns of allosteric interactions may further augment the predictive abilities of AlphaFold methods for modeling of alternative protein sates, conformational ensembles and mutation-induced structural transformations.

biophysics↗

Predicting Functional Conformational Ensembles and Binding Mechanisms of Convergent Evolution for SARS-CoV-2 Spike Omicron Variants Using AlphaFold2 Sequence Scanning Adaptations and Molecular Dynamics Simulations

In this study, we combined AlphaFold-based approaches for atomistic modeling of multiple protein states and microsecond molecular simulations to accurately characterize conformational ensembles and binding mechanisms of convergent evolution for the SARS-CoV-2 Spike Omicron variants BA.1, BA.2, BA.2.75, BA.3, BA.4/BA.5 and BQ.1.1. We employed and validated several different adaptations of the AlphaFold methodology for modeling of conformational ensembles including the introduced randomized full sequence scanning for manipulation of sequence variations to systematically explore conformational dynamics of Omicron Spike protein complexes with the ACE2 receptor. Microsecond atomistic molecular dynamic simulations provide a detailed characterization of the conformational landscapes and thermodynamic stability of the Omicron variant complexes. By integrating the predictions of conformational ensembles from different AlphaFold adaptations and applying statistical confidence metrics we can expand characterization of the conformational ensembles and identify functional protein conformations that determine the equilibrium dynamics for the Omicron Spike complexes with the ACE2. Conformational ensembles of the Omicron RBD-ACE2 complexes obtained using AlphaFold-based approaches for modeling protein states and molecular dynamics simulations are employed for accurate comparative prediction of the binding energetics revealing an excellent agreement with the experimental data. In particular, the results demonstrated that AlphaFold-generated extended conformational ensembles can produce accurate binding energies for the Omicron RBD-ACE2 complexes. The results of this study suggested complementarities and potential synergies between AlphaFold predictions of protein conformational ensembles and molecular dynamics simulations showing that integrating information from both methods can potentially yield a more adequate characterization of the conformational landscapes for the Omicron RBD-ACE2 complexes. This study provides insights in the interplay between conformational dynamics and binding, showing that evolution of Omicron variants through acquisition of convergent mutational sites may leverage conformational adaptability and dynamic couplings between key binding energy hotspots to optimize ACE2 binding affinity and enable immune evasion.

biophysics↗

Interpretable Atomistic Prediction and Functional Analysis of Conformational Ensembles and Allosteric States in Protein Kinases Using AlphaFold2 Adaptation with Randomized Sequence Scanning and Local Frustration Profiling

The groundbreaking achievements of AlphaFold2 (AF2) approaches in protein structure modeling marked a transformative era in structural biology. Despite the success of AF2 tools in predicting single protein structures, these methods showed intrinsic limitations in predicting multiple functional conformations of allosteric proteins and fold-switching systems. The recent NMR-based structural determination of the unbound ABL kinase in the active state and two inactive low-populated functional conformations that are unique for ABL kinase presents an ideal challenge for AF2 approaches. In the current study we employ several implementations of AF2 methods to predict protein conformational ensembles and allosteric states of the ABL kinase including (a) multiple sequence alignments (MSA) subsampling approach; (b) SPEACH_AF approach in which alanine scanning is performed on generated MSAs; and (c) introduced in this study randomized full sequence mutational scanning for manipulation of sequence variations combined with the MSA subsampling. We show that the proposed AF2 adaptation combined with local frustration mapping of conformational states enable accurate prediction of the ABL active and intermediate structures and conformational ensembles, also offering a robust approach for interpretable characterization of the AF2 predictions and limitations in detecting hidden allosteric states. We found that the large high frustration residue clusters are uniquely characteristic of the low-populated, fully inactive ABL form and can define energetically frustrated cracking sites of conformational transitions, presenting difficult targets for AF2 methods. This study uncovered previously unappreciated, fundamental connections between distinct patterns of local frustration in functional kinase states and AF2 successes/limitations in detecting low-populated frustrated conformations, providing a better understanding of benefits and limitations of current AF2-based adaptations in modeling of conformational ensembles.

biophysics↗

Microsecond Molecular Dynamics Simulations and Markov State Models of Mutation-Induced Allosteric Mechanisms for the Light-Oxygen-Voltage 2 Protein : Revealing Structural Basis of Signal Transmission Induced by Photoactivation of the Light Protein State

Avena Sativa phototropin 1 Light-oxygen-voltage 2 domain (AsLOV2) is the model protein of Per-Arnt-Sim (PAS) superfamily, characterized by conformational changes in response to external environmental stimuli. This conformational change is initiated by the unfolding of the N-terminal helix in the dark state followed by the unfolding of the C-terminal helix. The light state is defined by the unfolded termini and the subsequent modifications in hydrogen bond patterns. In this photoreceptor, {beta}-sheets have been identified as crucial components for mediating allosteric signal transmission between the two termini. In this study, we combined microsecond all-atm molecular dynamics simulations and Markov state modeling of conformational states to quantify molecular basis of mutation-induced allostery in the AsLOV2 protein. Through a combination of computational investigations, we determine that the H{beta} and I{beta} strands are the most critical structural elements involved in the allosteric mechanism. To elucidate the role of these {beta}-sheets, we introduced 13 distinct mutations (F490L, N492A, L493A, F494L, H495L, L496F, Q497A, R500A, F509L, Q513A, L514A, D515V, and T517V) and conducted comprehensive simulation analysis. The results highlighted the role of two hydrogen bond Asn482-Leu453 and Gln479-Val520 in the observed distinct behaviors of L493A, L496F, Q497A, and D515V mutants. The comprehensive atomistic-level analysis of the conformational landscapes revealed the critical functional role of {beta}-sheet segments in the transmission of the allosteric signal upon the photoactivation of the light state.

biophysics↗

AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance

In this study, we combined AI-based atomistic structural modeling and microsecond molecular simulations of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for XBB.1.5+L455F, XBB.1.5+F456L(EG.5) and XBB.1.5+L455F/F456L (FLip) lineages to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and physics-based rigorous computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of Q493 hotspot in synchronization of epistatic couplings between L455F and F456L mutations providing a quantitative insight into the mechanism underlying differences between XBB lineages. Mutational profiling is combined with network-based model of epistatic couplings showing that the Q493, L455 and F456 sites mediate stable communities at the binding interface with ACE2 and can serve as stable mediators of non-additive couplings. Structure-based mutational analysis of Spike protein binding with the class 1 antibodies quantified the critical role of F456L and F486P mutations in eliciting strong immune evasion response. The results of this analysis support a mechanism in which the emergence of EG.5 and FLip variants may have been dictated by leveraging strong epistatic effects between several convergent revolutionary hotspots that provide synergy between the improved ACE2 binding and broad neutralization resistance. This interpretation is consistent with the notion that functionally balanced substitutions which simultaneously optimize immune evasion and high ACE2 affinity may continue to emerge through lineages with beneficial pair or triplet combinations of RBD mutations involving mediators of epistatic couplings and sites in highly adaptable RBD regions.

biophysics↗

Accurate Characterization of Conformational Ensembles and Binding Mechanisms of the SARS-CoV-2 Omicron BA.2 and BA.2.86 Spike Protein with the Host Receptor and Distinct Classes of Antibodies Using AlphaFold2-Augmented Integrative Computational Modeling

The latest wave SARS-CoV-2 Omicron variants displayed a growth advantage and the increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with all-atom MD simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that AlphaFold2-predicted conformational ensemble of the BA.2.86 spike protein complex can accurately capture the main dynamics signatures obtained from microscond molecular dynamics simulations. The ensemble-based dynamic mutational scanning of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 dissected the role of the BA.2 and BA.2.86 backgrounds in modulating binding free energy changes revealing a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 mutational sites R403K, F486P and R493Q. To examine immune evasion properties of BA.2.86 in atomistic detail, we performed large scale structure-based mutational profiling of the S protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against BA.2.86 variant. The results quantified specific function of the BA.2.86 mutations to ensure broad resistance against different classes of RBD antibodies. This study revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have primarily evolved to improve immune escape while modulating binding affinity with ACE2 through cooperative effect of R403K, F486P and R493Q mutations. The study supports a hypothesis that the impact of the increased ACE2 binding affinity on viral fitness is more universal and is mediated through cross-talk between convergent mutational hotspots, while the effect of immune evasion could be more variant-dependent.

biophysics↗

Examining Functional Linkages Between Conformational Dynamics, Protein Stability and Evolution of Cryptic Binding Pockets in the SARS-CoV-2 Omicron Spike Complexes with the ACE2 Host Receptor: Recombinant Omicron Variants Mediate Variability of Conserved Allosteric Sites and Binding Epitopes

In the current study, we explore coarse-grained simulations and atomistic molecular dynamics together with binding energetics scanning and cryptic pocket detection in a comparative examination of conformational landscapes and systematic characterization of allosteric binding sites in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB.1 spike full-length trimer complexes with the host receptor ACE2. Microsecond simulations, Markov state models and mutational scanning of binding energies of the SARS-CoV-2 BA.2 and BA.2.75 receptor binding domain complexes revealed the increased thermodynamic stabilization of the BA.2.75 variant and significant dynamic differences between these Omicron variants. Molecular simulations of the SARS-CoV-2 Omicron spike full length trimer complexes with the ACE2 receptor complemented atomistic studies and enabled an in-depth analysis of mutational and binding effects on conformational dynamic and functional adaptability of the Omicron variants. Despite considerable structural similarities, Omicron variants BA.2, BA.2.75 and XBB.1 can induce unique conformational dynamic signatures and specific distributions of the conformational states. Using conformational ensembles of the SARS-CoV-2 Omicron spike trimer complexes with ACE2, we conducted a comprehensive cryptic pocket screening to examine the role of Omicron mutations and ACE2 binding on the distribution and functional mechanisms of the emerging allosteric binding sites. This analysis captured all experimentally known allosteric sites and discovered networks of inter-connected and functionally relevant allosteric sites that are governed by variant-sensitive conformational adaptability of the SARS-CoV-2 spike structures. The results detailed how ACE2 binding and Omicron mutations in the BA.2, BA.2.75 and XBB.1 spike complexes modulate the distribution of conserved and druggable allosteric pockets harboring functionally important regions. The results of are significant for understanding functional roles of druggable cryptic pockets that can be used for allostery-mediated therapeutic intervention targeting conformational states of the Omicron variants.

biophysics↗

Defense mechanism of a bacterial retron supramolecular assembly

Retrons are a class of multigene antiphage defense system typically consisting of a retron reverse transcriptase, a non-coding RNA, and a cognate effector. Although the triggers for several retron systems have been discovered recently, the full picture of how retron systems sense invading phages and mediate defense remains to be elucidated. Here, we focus on the retron Ec86 defense system and report its modes of activation and action. We identified a phage-encoded DNA cytosine methyltransferase (Dcm) as the trigger of the Ec86 system and show that Ec86 senses msDNA methylation and becomes activated. We further determined the structure of a tripartite retron Ec86 supramolecular assembly, which is primed for activation by Dcm, and demonstrated that the activated system confers defense through depletion of nucleoside derivatives. These findings emphasize the role of retrons being a second line of defense and highlight an emerging theme of anti-phage defense through supramolecular complex assemblies.

microbiology↗

BacScan: An Unbiased and Genome-Wide Approach to Identify Bacterial Highly Immunogenic Proteins

Bacterial pathogens are the second leading cause of death worldwide. However, the development of bacterial vaccines has been challenged by the presence of multiple serotypes and the lack of cross-protection between serotypes. Therefore, there is an urgent need to identify protective antigens conserved across serotypes in order to develop a broadly protective vaccine. Here, we have developed an unbiased and genome-wide technique, BacScan, which uses bacterial-specific serum to rapidly identify highly conserved immunogenic proteins by combining phage display, immunoprecipitation, and next-generation sequencing. As a proof of concept, we identified 19 highly immunogenic proteins from Streptococcus suis core proteins. Immunoreactivity analysis of mouse, pig, and human sera indicated that 2 proteins could be the potential targets for the development of serological diagnostics. Eight proteins provided 20%-100% protection against S. suis challenge in immunized animals, indicating the potential vaccine targets. BacScan can be applied to any bacterial pathogen and has the potential to accelerate the development of a broadly protective bacterial vaccine. TeaserA novel method to identify the highly conserved immunogenic bacterial proteins as targets for the development a broadly protective bacterial vaccine.

microbiology↗

Markov State Models and Perturbation-Based Approaches Reveal Distinct Dynamic Signatures and Hidden Allosteric Pockets in the Emerging SARS-Cov-2 Spike Omicron Variants Complexes with the Host Receptor: The Interplay of Dynamics and Convergent Evolution Modulates Allostery and Functional Mechanisms

The new generation of SARS-CoV-2 Omicron variants displayed a significant growth advantage and the increased viral fitness by acquiring convergent mutations, suggesting that the immune pressure can promote convergent evolution leading to the sudden acceleration of SARS-CoV-2 evolution. In the current study, we combined structural modeling, extensive microsecond MD simulations and Markov state models to characterize conformational landscapes and identify specific dynamic signatures of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the recently emerged highly transmissible XBB.1, XBB.1.5, BQ.1, and BQ.1.1 Omicron variants. Microsecond simulations and Markovian modeling provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the XBB.1.5 subvariant which is contrasted to more dynamic BQ.1 and BQ.1.1 subvariants. Despite considerable structural similarities, Omicron mutations can induce unique dynamic signatures and specific distributions of conformational states. The results suggested that variant-specific changes of conformational mobility in the functional interfacial loops of the spike receptor binding domain can be fine-tuned through cross-talk between convergent mutations thereby providing an evolutionary path for modulation of immune escape. By combining atomistic simulations and Markovian modeling analysis with perturbation-based approaches, we determined important complementary roles of convergent mutation sites as effectors and receivers of allosteric signaling involved in modulating conformational plasticity at the binding interface and regulating allosteric responses. This study also characterized the dynamics-induced evolution of allosteric pockets in the Omicron complexes that revealed hidden allosteric pockets and suggested that convergent mutation sites could control evolution and distribution of allosteric pockets through modulation of conformational plasticity in the flexible adaptable regions. Through integrative computational approaches, this investigation provides a systematic analysis and comparison of the effects of Omicron subvariants on conformational dynamics and allosteric signaling in the complexes with the ACE2 receptor. For Table of Contents Use Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/541592v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@2729a7org.highwire.dtl.DTLVardef@11fa88forg.highwire.dtl.DTLVardef@1737e4eorg.highwire.dtl.DTLVardef@1695eb6_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗